# Investigating Value of Information in Future Vehicular Communications

## TL;DR

This paper explores how to evaluate and prioritize data in future vehicular networks to ensure critical information is transmitted efficiently amid capacity constraints.

## Contribution

It introduces a method to quantify the value of information in vehicular networks and proposes decision processes for efficient data dissemination.

## Key findings

- VoI can be characterized using analytic hierarchy processes.
- Prioritization improves data transmission efficiency.
- Simulation results demonstrate effective VoI-based dissemination.

## Abstract

The next generations of vehicles are expected to be equipped with sophisticated sensors to support advanced automotive services. The large volume of data generated by such applications will likely put a strain on the vehicular communication technologies, which may be unable to guarantee the required quality of service. In this scenario, it is fundamental to assess the value of information (VoI) provided by each data source, to prioritize the transmissions that have greatest importance for the target applications. In this paper, we characterize VoI in future vehicular networks, and investigate efficient data dissemination methods to tackle capacity issues. Through a simulation study, we show how analytic hierarchy multicriteria decision processes can be exploited to determine the value of sensory observations as a function of space, time, and quality criteria.